System Bits: July 3

Machine learning network for personalized autism therapyMIT Media Lab researchers have developed a personalized deep learning network for therapy use with children with autism spectrum conditions.

They reminded these children often have trouble recognizing the emotional states of people around them, such as distinguishing a happy face from a fearful face. To help with this, some therapists use a kid-friendly robot to demonstrate those emotions and to engage the children in imitating the emotions and responding to them in appropriate ways.

An example of a therapy session augmented with humanoid robot NAO [SoftBank Robotics], which was used in the EngageMe study. Tracking of limbs/faces was performed using the CMU Perceptual Lab’s OpenPose utility.Source: MIT Media Lab

The team said this type of therapy works best if the robot can smoothly interpret the child’s own behavior — whether he or she is interested and excited or paying attention — during the therapy so this personalized machine learning technique helps robots estimate the engagement and interest of each child during these interactions, using data that are unique to that child. With this personalized “deep learning” network, the robots’ perception of the children’s responses agreed with assessments by human experts, with a correlation score of 60 percent, the researchers reported.

In comparison, because it can be challenging for human observers to reach high levels of agreement about a child’s engagement and behavior, their correlation scores are usually between 50 and 55 percent. The MIT team believes that robots trained on human observations, as in this study, could someday provide more consistent estimates of these behaviors in order to augment human therapists with key information that can be used to personalize therapy content.

Low-cost plastic sensors for monitoring health conditions
A team led by the University of Cambridge and King Abdullah University of Science and Technology (KAUST) has developed a low-cost sensor made from semiconducting plastic that can be used to diagnose or monitor a wide range of health conditions, such as surgical complications or neurodegenerative diseases.

The team said the sensor can measure the amount of critical metabolites, such as lactate or glucose, that are present in sweat, tears, saliva or blood, and, when incorporated into a diagnostic device, could allow health conditions to be monitored quickly, cheaply and accurately. The new device has a far simpler design than existing sensors, and opens up a wide range of new possibilities for health monitoring down to the cellular level.

Polymer biosensorSource: KAUST

Semiconducting plastics such as those used in the current work are being developed for use in solar cells and flexible electronics, but have not yet seen widespread use in biological applications.

Dr. Anna-Maria Pappa, a postdoctoral researcher in Cambridge’s Department of Chemical Engineering and Biotechnology, and lead researcher said, “In our work, we’ve overcome many of the limitations of conventional electrochemical biosensors that incorporate enzymes as the sensing material. In conventional biosensors, the communication between the sensor’s electrode and the sensing material is not very efficient, so it’s been necessary to add molecular wires to facilitate and ‘boost’ the signal.”

Dr. Anna-Maria Pappa, a postdoctoral researcher in Cambridge’s Department of Chemical Engineering and BiotechnologySource: University of Cambridge

To build their sensor, Pappa said she and her colleagues used a newly-synthesized polymer developed at Imperial College that acts as a molecular wire, directly accepting the electrons produced during electrochemical reactions. When the material comes into contact with a liquid such as sweat, tears or blood, it absorbs ions and swells, becoming merged with the liquid. This leads to significantly higher sensitivity compared to traditional sensors made of metal electrodes.

Additionally, when the sensors are incorporated into more complex circuits, such as transistors, the signal can be amplified and respond to tiny fluctuations in metabolite concentration, despite the tiny size of the devices.

Initial tests of the sensors were used to measure levels of lactate, which is useful in fitness applications or to monitor patients following surgery. However, according to the researchers, the sensor can be easily modified to detect other metabolites, such as glucose or cholesterol by incorporating the appropriate enzyme, and the concentration range that the sensor can detect can be adjusted by changing the device’s geometry, the team said.

“This is the first time that it’s been possible to use an electron accepting polymer that can be tailored to improve communication with the enzymes, which allows for the direct detection of a metabolite: this hasn’t been straightforward until now. It opens up new directions in biosensing, where materials can be designed to interact with a specific metabolite, resulting in far more sensitive and selective sensors,” Pappa added.

Monitoring intraocular pressure
To help prevent permanent damage to the optic nerve as the result of glaucoma, Fraunhofer IMS researchers have developed a microsensor system that monitors the pressure level in the eye and its fluctuation over time.

The team reminded that people afflicted with glaucoma are generally unaware of the condition in the early stages so it goes unnoticed until it kills enough optic nerve cells to impair vision. Intraocular pressure has to be brought down and kept in the normal range to prevent glaucoma from spreading and causing further damage. This can be done with medication, eye drops or, in advanced stages, with surgery. Choosing the right therapy is paramount when treating glaucoma, which is why the treating physician must know the pressure level in the eye.

Prevailing measurement methods are poorly suited to gather enough data so as to reveal meaningful insights given that these measurements are usually taken in a doctor’s office, with too much time elapsing between sessions. Further, pressure can rise to harmfully high levels several times a day, so the likelihood of these readings going undetected is very high, which increases the risk of a physician opting for the wrong therapy many times over.

Now scientists at Fraunhofer IMS have managed to solve this problem. In a joint effort with Implandata, they developed EYEMATE, a microsensor system that enables patients to take contactless pressure measurements of their own eyes at any chosen frequency.

Fraunhofer explained further that a sensor implanted in the eye gauges pressure and temperature. A hand-held reader records, digitizes and displays results; all the patient has to do is hold it in front of his or her eye. It takes the eye’s pressure and temperature readings in a matter of seconds – precisely, at any time and without touching the eye. With a data pool many times larger than what with conventional techniques can gather, attending physicians can apply the right therapy right away. The device’s readings can be downloaded, digitized and uploaded to cloud memory. The attending physician can access patient data at any time to check and assess the disease’s progression and, if necessary, adjust the therapy on the spot. The patient no longer has to stop by the practice to this end. Patients may also access these data directly via a smartphone app, track their intraocular pressure readings and take the appropriate action if the pressure rising to alarming levels. The benefits increase with frequent application: the more often the patient uses the reader, the more meaningful the readings and the more personalized the therapy options.

Fraunhofer IMS in Duisburg developed the semiconductor circuit that serves as an intraocular pressure sensor. It is a passive microsensor activated by the reader.

Implandata received CE approval for the sensor system in mid-2017 after the intraocular pressure sensor was validated in a clinical study at several hospitals in Germany.